An air suspension system-based automatic sun visor adjusting method and system for a vehicle

Abstract

The application relates to an air suspension system-based automatic sun visor adjusting method and system of a vehicle, which comprises the following steps: Q1. The vehicle runs on a road, real-time folding angle data information of a sun visor is acquired based on an angle sensor on the sun visor, real-time position data information of a human eye is acquired based on a vehicle-mounted DMS camera, real-time position data information of a seat is acquired based on a vehicle-mounted seat controller, real-time data information of a vehicle body slope and six-direction acceleration is acquired based on a vehicle-mounted electronic stability component, and real-time height data information of the vehicle body is acquired based on a vehicle air suspension system. The application not only solves the problem that the sun visor angle cannot be automatically adjusted with seat adjustment and vehicle condition change during vehicle running, but also avoids the need of the driver to frequently adjust the sun visor angle due to uphill and downhill or seat adjustment during vehicle running, so that the driving safety is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sun visor, in particular to an automatic adjusting method and system of sun visor based on air suspension system. BACKGROUND

[0002] During driving, the driver will inevitably encounter the scene of the sun shining in front of him. At this time, because of the glare of the sun, the driver cannot observe the traffic situation on the road, and if there are other vehicles or pedestrians and other traffic participants with sudden conditions, it is easy to cause accidents due to the delay of the driver's response.

[0003] Based on the above situation, a sun visor is arranged in front of the head of the driver, and the initial state of the sun visor is attached to the roof of the vehicle. When in use, it is manually adjusted to rotate around the Y-axis of the vehicle, so as to block the glaring light in front of the vehicle. After rotating around the Y-axis to the appropriate position, it can also be adjusted to rotate around the Z-axis of the vehicle, and placed in the appropriate position to block the glaring light on the left side of the driver.

[0004] Prior art one, Chinese patent application (application number: 201620396381.4) discloses a sun visor adjusting device and a car. The sun visor adjusting device comprises a central controller, a GPS positioning component, a light sensor assembly, a face recognition assembly and a sun visor driving assembly connected with the central controller. The sun visor adjusting device can automatically adjust the position of the sun visor according to the position of the vehicle, the intensity of sunlight, the azimuth of the sun and the relative position information of the eye. Limited by the accuracy of GPS, the angle of the sun changes when the vehicle goes uphill or downhill, and the system cannot automatically adjust the angle of the sun visor. The user needs to manually adjust it. Limited by the technology of the vehicle face recognition camera, the system cannot recognize the movement of the eye in the direction of the axis connecting the camera, so it cannot automatically adjust according to the change of the position of the eye.

[0005] In the prior art two, Chinese patent application (application number: 201620739920.X) discloses a control device of automobile sun visor and automobile, the control device of automobile sun visor includes: image sensor, for carrying out face image acquisition to passenger;Face recognition module, for identifying the identity information of passenger according to the face image collected by the image sensor;Face brightness state determination module, for determining the brightness state of the face area of passenger according to the face image collected by the image sensor;Sun visor motor controller, for determining the angle of sun visor according to the identity information and the brightness state, and sending driving instruction to sun visor motor;The sun visor motor is used for receiving driving instruction, and adjusting sun visor to the angle according to the driving instruction, the face brightness state does not refer to, cannot accurately identify, judges the whole face brightness, and does not match the demand of actually shielding eye parts, and instead easily shields the line of sight of driver. SUMMARY

[0006] In view of the deficiencies of the above prior art, the present application provides an automobile sun visor automatic adjustment method and system based on air suspension system, which not only solves the problem that the sun visor angle cannot be automatically adjusted during vehicle driving due to seat adjustment and vehicle condition change, but also avoids the need for the driver to frequently adjust the sun visor angle during vehicle driving due to uphill or downhill or seat adjustment, thereby improving driving safety.

[0007] In order to achieve the above-mentioned purpose and other related purposes, the technical scheme provided by the present application is as follows:

[0008] An automobile sun visor automatic adjustment method based on air suspension system, the method comprises:

[0009] Q1. The vehicle is driving on the road, the folding angle data information of the sun visor is obtained in real time based on the angle sensor on the sun visor, the position data information of the human eye is obtained in real time based on the vehicle-mounted DMS camera, the position data information of the seat is obtained in real time based on the vehicle-mounted seat controller, the data information of the vehicle body slope and six-direction acceleration is obtained in real time based on the vehicle-mounted electronic stability component, and the height data information of the vehicle body is obtained in real time based on the vehicle air suspension system;

[0010] Q2. Based on the position data information of the seat, the data information of the vehicle body slope and six-direction acceleration and the height data information of the vehicle body, a damping trend prediction model of vehicle state based on golden sine factor is constructed, the state of the vehicle is predicted, and the state data information of the predicted vehicle is obtained;

[0011] Q3. Based on the predicted vehicle state data information, the sun visor folding angle data information and the human eye position data information, the folding angle of the sun visor is optimized by using an Archimedean optimization algorithm fused with Momentum and RMSProp parameters, and the optimized sun visor folding angle data information is obtained.

[0012] Q4. Based on the optimized sun visor folding angle data information, a sun visor folding angle feasibility function P is established to evaluate the feasibility of the sun visor folding angle, and the sun visor folding angle feasibility evaluation data information is obtained.

[0013] Further, the sun visor folding angle feasibility function P is,

[0014] ,

[0015] Wherein, x is the optimized sun visor folding angle data information, ω1, ω2 and ω3 are the feasibility evaluation factors of the sun visor folding angle.

[0016] Further, the constraint conditions of the feasibility evaluation factors ω1, ω2 and ω3 of the sun visor folding angle are,

[0017] ,

[0018] ,

[0019] Wherein, x is the optimized sun visor folding angle data information.

[0020] Further, the method further comprises:

[0021] Q5. Based on the sun visor folding angle feasibility evaluation data information, a preset threshold is set, if the sun visor folding angle feasibility evaluation data information is less than the preset threshold, the sun visor folding angle meets the requirements, and the optimized sun visor folding angle data information is output, if the sun visor folding angle feasibility evaluation data information is greater than the preset threshold, the sun visor folding angle does not meet the requirements, and returns to step Q3.

[0022] Further, in step Q2, the construction of the vehicle state damping trend prediction model based on the golden sine factor, the state of the vehicle is predicted, which comprises:

[0023] Q21. Based on the seat position data information, the vehicle body slope and six direction acceleration data information and the vehicle body height data information, a multivariate relationship function W of vehicle data is constructed,

[0024] ,

[0025] wherein, y1 is position data information of the seat, y2 is data information of the body slope and six-direction acceleration, y3 is height data information of the vehicle body, σ1, σ2 and σ3 are correlation adjustment factors of the vehicle data, which represent the correlation of the vehicle data, and correlation data information of the vehicle data is obtained;

[0026] Q22. Based on the correlation data information of the vehicle data, a vehicle state damping trend prediction function R based on the golden sine factor is established,

[0027] ,

[0028] wherein, z is the correlation data information of the vehicle data, ρ1, ρ2 and ρ3 are the golden sine factors of the vehicle state, α is the smoothing parameter of the level of the vehicle state, β is the smoothing parameter of the trend of the vehicle state, and δ is the damping parameter of the vehicle state;

[0029] Q23. Based on the vehicle state damping trend prediction function R based on the golden sine factor, the state of the vehicle is predicted, and the state data information of the predicted vehicle is obtained.

[0030] Further, the golden sine factors ρ1, ρ2 and ρ3 of the vehicle state are,

[0031] ,

[0032] ,

[0033] ,

[0034] The constraint conditions of the smoothing parameter α of the level of the vehicle state, the smoothing parameter β of the trend of the vehicle state and the damping parameter δ of the vehicle state are,

[0035] .

[0036] Further, in step Q3, the Archimedes optimization algorithm fused with Momentum and RMSProp parameters is used to optimize the folding angle of the sun visor, comprising:

[0037] Q31. Based on the state data information of the predicted vehicle, the folding angle data information of the sun visor and the position data information of the human eye, the population is initialized, the population parameters and the maximum iteration number are determined, and the initialized population data information is obtained;

[0038] Q32. Based on the initialized population data information, an individual fitness function S of the population is established,

[0039] ,

[0040] Wherein, r is the initialized population data information, γ1, γ2 and γ3 are the fitness determination factors of the population individuals, the fitness value of the population individuals is calculated, and the fitness value data information of the population individuals is obtained;

[0041] Q33. Based on the fitness value data information of the population individuals, a target optimization function G is established,

[0042] ,

[0043] Wherein, a is the fitness value data information of the population individuals, η1 is the Momentum parameter of the population individuals, η2 is the RMSProp parameter of the population individuals, and η3 is the covariance constant parameter of the population individuals. The folding angle of the sun shield is optimized, and the folding angle data information of the optimized sun shield is obtained.

[0044] Further, the Momentum parameter η1 of the population individuals is,

[0045] ,

[0046] The RMSProp parameter η2 of the population individuals is,

[0047] ,

[0048] The covariance constant parameter η3 of the population individuals is,

[0049] ,

[0050] Wherein, a is the fitness value data information of the population individuals.

[0051] In order to achieve the above-mentioned purpose and other related purposes, the present application also provides a system for realizing any one of the air suspension system based automobile sun shield automatic adjusting method, the system comprises:

[0052] A DMS camera is used to collect human eye position information;

[0053] A seat controller is used to acquire current seat position information in real time, and the seat position information includes seat front and rear position information, seat height information and seat backrest angle information;

[0054] An electronic stability component is used to acquire current vehicle body slope information and six-direction acceleration information in real time;

[0055] A sun shield motor and a sun shield connected with the sun shield motor are used to acquire folding angle information of the sun shield in real time and drive to change the folding angle of the sun shield;

[0056] The sun visor controller is connected with the DMS camera, the seat controller, the electronic stability component and the sun visor motor respectively, and outputs and feeds back the folding angle information of the sun visor to the sun visor motor in combination with the body height information provided by the air suspension system, the controller comprises a PCB board, a plastic shell and a low-voltage connector PIN, the PCB board is arranged in the plastic shell, and the low-voltage connector PIN is arranged on the outside of the plastic shell.

[0057] Further, the seat controller comprises:

[0058] A seat front and rear position sensor is arranged for acquiring real-time current seat front and rear position information;

[0059] A seat height sensor is arranged for acquiring real-time current seat height information;

[0060] A seat backrest angle sensor is arranged for acquiring real-time current seat backrest angle information;

[0061] The electronic stability component comprises:

[0062] An accelerometer is arranged for acquiring current six-directional acceleration information of the vehicle;

[0063] A sensing gyroscope is arranged for acquiring current vehicle body slope information.

[0064] The present application has the following positive effects:

[0065] 1. The present application predicts the state of the vehicle by constructing a damping trend prediction model based on the golden sine factor, and optimizes the folding angle of the sun visor by using the Archimedes optimization algorithm fused with Momentum and RMSProp parameters, to obtain the optimized folding angle data information of the sun visor, which not only solves the problem that the sun visor angle cannot be automatically adjusted during vehicle driving due to seat adjustment and vehicle condition changes, but also avoids the need for the driver to frequently adjust the sun visor angle during vehicle driving due to uphill or downhill driving or seat adjustment, thereby improving driving safety.

[0066] 2. The present application establishes a sun visor folding angle feasibility function P to evaluate the feasibility of the folding angle of the sun visor, to obtain the sun visor folding angle feasibility evaluation data information, and judges the feasibility of the folding angle of the sun visor by setting a preset threshold, which not only prevents the folding angle of the sun visor from being exceeded, thereby causing damage to the sun visor, but also further improves the user's experience. BRIEF DESCRIPTION OF DRAWINGS

[0067] Figure 1 The present application is a method flowchart;

[0068] Figure 2 This is a schematic diagram of the process for constructing a damping trend prediction model for vehicle state based on the golden sine factor according to the present invention.

[0069] Figure 3 This is a flowchart illustrating the Archimedes optimization algorithm of the present invention, which incorporates Momentum and RMSProp parameters.

[0070] Figure 4 This is a schematic diagram of the system framework of the present invention;

[0071] Figure 5 This is a schematic diagram of the structure of the sunshade controller of the present invention;

[0072] Figure 6 for Figure 5 A schematic diagram of the cross-sectional structure;

[0073] Figure 7 This is a schematic diagram (a) of the automatic adjustment process of the present invention;

[0074] Figure 8 This is a schematic diagram (II) of the automatic adjustment process of the present invention;

[0075] Figure 9 This is a schematic diagram (III) of the automatic adjustment process of the present invention.

[0076] The following are the labels in the diagram: 11—DMS camera, 12—seat controller, 13—electronic stabilization component, 14—sun visor motor, 141—sun visor, 15—controller, 151—PCB board, 152—plastic housing, 153—low-voltage connector PIN, 154—groove, 16—DMS detection module. Detailed Implementation

[0077] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings. Preferred embodiments of this application are shown in the drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of this application.

[0078] Example 1: As Figure 1 As shown, an automatic adjustment method for a car sun visor based on an air suspension system is disclosed, the method comprising:

[0079] Q1. The vehicle is driving on the road, the folding angle data information of the sun visor is obtained in real time based on the angle sensor on the sun visor, the position data information of the human eye is obtained in real time based on the vehicle-mounted DMS camera, the position data information of the seat is obtained in real time based on the vehicle-mounted seat controller, the data information of the body slope and six-direction acceleration is obtained in real time based on the vehicle-mounted electronic stability component, and the height data information of the vehicle body is obtained in real time based on the vehicle air suspension system;

[0080] Q2. Based on the position data information of the seat, the data information of the body slope and six-direction acceleration, and the height data information of the vehicle body, a damping trend prediction model of the vehicle state based on the golden sine factor is constructed, the state of the vehicle is predicted, and the state data information of the predicted vehicle is obtained;

[0081] Q3. Based on the state data information of the predicted vehicle, the folding angle data information of the sun visor, and the position data information of the human eye, an Archimedes optimization algorithm fused with Momentum and RMSProp parameters is used to optimize the folding angle of the sun visor, and the optimized folding angle data information of the sun visor is obtained;

[0082] Q4. Based on the optimized folding angle data information of the sun visor, a sun visor folding angle feasibility function P is established, the feasibility of the folding angle of the sun visor is evaluated, and the sun visor folding angle feasibility evaluation data information is obtained.

[0083] In this embodiment, the sun visor folding angle feasibility function P is,

[0084] ,

[0085] Wherein, x is the optimized folding angle data information of the sun visor, ω1, ω2 and ω3 are the feasibility evaluation factors of the sun visor folding angle.

[0086] In this embodiment, the constraint conditions of the feasibility evaluation factors ω1, ω2 and ω3 of the sun visor folding angle are,

[0087] ,

[0088] ,

[0089] Wherein, x is the optimized folding angle data information of the sun visor.

[0090] In this embodiment, the method further comprises:

[0091] Q5. Based on the sun visor folding angle feasibility assessment data information, a preset threshold is set, if the sun visor folding angle feasibility assessment data information is less than the preset threshold, the sun visor folding angle meets the requirements, and the optimized sun visor folding angle data information is output, if the sun visor folding angle feasibility assessment data information is greater than the preset threshold, the sun visor folding angle does not meet the requirements, and returns to step Q3.

[0092] In this embodiment, as shown in step Q2, the damping trend prediction model of the vehicle state based on the golden sine factor is constructed, and the state of the vehicle is predicted, including: Figure 2

[0093] Q21. Based on the seat position data information, the vehicle body slope and six-direction acceleration data information, and the vehicle body height data information, a multivariate relationship function W of vehicle data is constructed,

[0094] ,

[0095] Wherein, y1 is the seat position data information, y2 is the vehicle body slope and six-direction acceleration data information, y3 is the vehicle body height data information, σ1, σ2 and σ3 are the correlation adjustment factors of vehicle data, which characterize the correlation of vehicle data, and the correlation data information of vehicle data is obtained;

[0096] Q22. Based on the correlation data information of vehicle data, a vehicle state damping trend prediction function R based on the golden sine factor is established,

[0097] ,

[0098] Wherein, z is the correlation data information of vehicle data, ρ1, ρ2 and ρ3 are the golden sine factors of vehicle state, α is the smoothing parameter of the level of vehicle state, β is the smoothing parameter of the trend of vehicle state, and δ is the damping parameter of vehicle state;

[0099] Q23. Based on the vehicle state damping trend prediction function R based on the golden sine factor, the state of the vehicle is predicted, and the predicted state data information of the vehicle is obtained.

[0100] Further, the golden sine factors ρ1, ρ2 and ρ3 of the vehicle state are,

[0101] ,

[0102] ,

[0103] ,

[0104] ​The constraint conditions of the smoothing parameter a of the level of the vehicle state, the smoothing parameter β of the trend of the vehicle state, and the damping parameter δ of the vehicle state are,

[0105] .

[0106] Embodiment 2: Based on the automatic adjustment method of the sun visor of the automobile based on the air suspension system in embodiment 1, the present application is further described and explained as follows.

[0107] As Figure 1 shown, an automatic adjustment method of a sun visor of an automobile based on an air suspension system, the method comprising:

[0108] Q1. The vehicle is driving on the road, the folding angle data information of the sun visor is obtained in real time based on the angle sensor on the sun visor, the position data information of the human eye is obtained in real time based on the vehicle-mounted DMS camera, the position data information of the seat is obtained in real time based on the vehicle-mounted seat controller, the data information of the body slope and six-direction acceleration is obtained in real time based on the vehicle-mounted electronic stability component, and the height data information of the vehicle body is obtained in real time based on the vehicle air suspension system;

[0109] Q2. Based on the position data information of the seat, the data information of the body slope and six-direction acceleration, and the height data information of the vehicle body, a damping trend prediction model of the vehicle state based on the golden sine factor is constructed, the state of the vehicle is predicted, and the data information of the state of the vehicle after prediction is obtained;

[0110] Q3. Based on the data information of the state of the vehicle after prediction, the folding angle data information of the sun visor, and the position data information of the human eye, the folding angle of the sun visor is optimized by using the Archimedes optimization algorithm fused with Momentum and RMSProp parameters, and the folding angle data information of the sun visor after optimization is obtained;

[0111] Q4. Based on the folding angle data information of the sun visor after optimization, a sun visor folding angle feasibility function P is established, the feasibility of the folding angle of the sun visor is evaluated, and the sun visor folding angle feasibility evaluation data information is obtained.

[0112] In this embodiment, as Figure 3 shown, in step Q3, the optimization of the folding angle of the sun visor by using the Archimedes optimization algorithm fused with Momentum and RMSProp parameters comprises:

[0113] Q31. Based on the data information of the state of the vehicle after prediction, the folding angle data information of the sun visor, and the position data information of the human eye, the population is initialized, the population parameters and the maximum number of iterations are determined, and the data information of the initialized population is obtained;

[0114] Q32. Based on the initialized population data information, the fitness function S of the population individual is established,

[0115] ,

[0116] Wherein r is the initialized population data information, γ1, γ2 and γ3 are the fitness determining factors of the population individual, the fitness value of the population individual is calculated, and the fitness value data information of the population individual is obtained;

[0117] Q33. Based on the fitness value data information of the population individual, the target optimization function G is established,

[0118] ,

[0119] Wherein a is the fitness value data information of the population individual, η1 is the Momentum parameter of the population individual, η2 is the RMSProp parameter of the population individual, η3 is the covariance constant parameter of the population individual, the folding angle of the sun shield is optimized, and the optimized folding angle data information of the sun shield is obtained.

[0120] In this embodiment, the Momentum parameter η1 of the population individual is,

[0121] ,

[0122] The RMSProp parameter η2 of the population individual is,

[0123] ,

[0124] The covariance constant parameter η3 of the population individual is,

[0125] ,

[0126] Wherein a is the fitness value data information of the population individual.

[0127] In this embodiment, as shown in Figure 4 An automatic adjusting device for automobile sun shield based on air suspension system, comprising:

[0128] DMS camera 11 for collecting human eye position information;

[0129] Seat controller 12 for real-time acquisition of current seat position information, the seat position information including seat front and rear position information, seat height information and seat backrest angle information;

[0130] Electronic stability component 13 for real-time acquisition of current vehicle body slope information and six-direction acceleration information;

[0131] The sun visor motor 14 and the sun visor 141 connected with the sun visor motor are used to obtain the sun visor folding angle information in real time and drive the sun visor folding angle to be changed;

[0132] The sun visor controller 15 is connected with the DMS camera 11, the seat controller 12, the electronic stability component 13 and the sun visor motor 14 respectively, and outputs and feeds back the sun visor folding angle information to the sun visor motor according to the four vehicle body height information provided by the air suspension system.

[0133] In the embodiment, as shown in Figure 5 The sun visor controller 15 includes a PCB board 151, a plastic shell 152 and a low-voltage connector PIN 153, the PCB board 151 is arranged inside the plastic shell 152, the plastic shell 152 is externally provided with the low-voltage connector PIN 153, the plastic shell 152 is in the shape of a cuboid, one side of the plastic shell 152 is provided with a groove 154, and the low-voltage connector PIN 153 is arranged in the groove 154.

[0134] The low-voltage connector PIN 153 is connected with the vehicle MCU, and the sun visor controller is arranged in the central console of the vehicle body.

[0135] In the embodiment, the seat controller 12 includes a seat front and rear position sensor, a seat height sensor and a seat backrest angle sensor, which are used to obtain the current seat front and rear position information, the current seat height information and the current seat backrest angle information in real time.

[0136] In the embodiment, the sun visor controller 15 further includes a DMS detection module 16 connected with the sun visor controller 15 and used to store and process the human eye position information collected by the DMS camera 11.

[0137] In the embodiment, the electronic stability component 13 includes an accelerometer and a sensing gyroscope, which are used to obtain the current six-direction acceleration information of the vehicle and the current vehicle body slope information.

[0138] In the embodiment, the application further provides an automobile including the automobile sun visor automatic adjusting device based on the air suspension system, and the automobile further includes a button used to turn on or turn off the automobile sun visor automatic adjusting device based on the air suspension system.

[0139] As shown in Figure 7 Or 8 or Figure 9As shown, firstly, it is judged whether the driver has manually opened the sun visor. If the user does not open it, it is judged that there is no sun visor adjustment requirement, and the function is in a suppression state. If the driver manually opens the sun visor, it is judged that the driver considers that there is glare at this time, and the sun visor needs to work. Then, the following information is collected: ① the angle a at which the sun visor is folded at this time; ② the front and rear position sensor / sitting height sensor / backrest angle sensor signal P(x, y) of the main driver seat; ③ the vehicle slope information Q(m, n) sent by the braking system; and ④ the suspension height sensor signal R(v, w) sent by the suspension system. The angle M of light irradiation at this time is calculated through signals ① to ④. The state information of signals ② to ④ at this time is memorized. It is judged that the state at this time is the best angle at which the sun visor just blocks the light irradiation to the eyes.

[0140] If the signals ② to ④ do not change, it is always in the detection state, unless the driver manually closes the sun visor, and then it is automatically exited.

[0141] If the signals ② to ④ change, the change values of the three signals are recorded, the position ΔP(x, y, z) of the middle point of the driver's eyes after the change is calculated, the angle β of the sun visor required for the light not to irradiate the eyes is calculated in combination with the calculated light irradiation angle M.

[0142] Among them, the angle adjustment function in the sun visor controller is β,

[0143] ,

[0144] Among them, (x, y, z) is the position coordinate of the middle point of the driver's eyes, (m, n) is the vehicle slope information, and (v, w) is the suspension height sensor signal.

[0145] Finally, the sun visor motor is driven to control the sun visor, so that the sun visor is adjusted from the angle a to the angle β.

[0146] In summary, the present application not only solves the problem that the sun visor angle cannot be automatically adjusted with the seat adjustment and vehicle condition change during vehicle driving, but also avoids the need for the driver to frequently adjust the sun visor angle during vehicle driving due to uphill or downhill or seat adjustment, thereby improving driving safety.

[0147] It should be understood that the application of the present application is not limited to the above examples, and those of ordinary skill in the art can make improvements or changes according to the above description, and all these improvements and changes shall belong to the protection scope of the claims attached to the present application.

Claims

1. An air suspension system-based automatic adjustment method for a sun visor of a vehicle, characterized by, The method comprises: Q1. The vehicle is driving on the road, the folding angle data information of the sun visor is obtained in real time based on the angle sensor on the sun visor, the position data information of the human eye is obtained in real time based on the vehicle-mounted DMS camera, the position data information of the seat is obtained in real time based on the vehicle-mounted seat controller, the data information of the body slope and six-direction acceleration is obtained in real time based on the vehicle-mounted electronic stability component, and the height data information of the vehicle body is obtained in real time based on the vehicle air suspension system; Q2. Based on the position data information of the seat, the data information of the body slope and six-direction acceleration, and the height data information of the vehicle body, a damping trend prediction model of the vehicle state based on the golden sine factor is constructed, the state of the vehicle is predicted, and the state data information of the predicted vehicle is obtained; Q3. Based on the state data information of the predicted vehicle, the folding angle data information of the sun visor, and the position data information of the human eye, the folding angle of the sun visor is optimized by using the Archimedes optimization algorithm fused with Momentum and RMSProp parameters, and the optimized folding angle data information of the sun visor is obtained; Q4. Based on the optimized folding angle data information of the sun visor, a sun visor folding angle feasibility function P is established, the feasibility of the folding angle of the sun visor is evaluated, and sun visor folding angle feasibility evaluation data information is obtained; The sun visor folding angle feasibility function P is, ， Wherein, x is the optimized folding angle data information of the sun visor, ω1, ω2 and ω3 are the feasibility evaluation factors of the sun visor folding angle; The constraint condition of the feasibility evaluation factors ω1, ω2 and ω3 of the sun visor folding angle is, ， ， Wherein, x is the optimized folding angle data information of the sun visor; In step Q2, the construction of the damping trend prediction model of the vehicle state based on the golden sine factor to predict the state of the vehicle comprises: Q21. Based on the position data information of the seat, the data information of the body slope and six-direction acceleration, and the height data information of the vehicle body, a multivariate relationship function W of vehicle data is constructed, ， Wherein, y1 is the position data information of the seat, y2 is the data information of the body slope and six-direction acceleration, y3 is the height data information of the vehicle body, σ1, σ2 and σ3 are the correlation adjustment factors of the vehicle data, which characterize the correlation of the vehicle data, and the correlation data information of the vehicle data is obtained; Q22. Based on the correlation data information of the vehicle data, a vehicle state damping trend prediction function R based on the golden sine factor is established, ， Wherein, z is the correlation data information of the vehicle data, ρ1, ρ2 and ρ3 are the golden sine factors of the vehicle state, α is the smoothing parameter of the level of the vehicle state, β is the smoothing parameter of the trend of the vehicle state, and δ is the damping parameter of the vehicle state; Q23. Based on the vehicle state damping trend prediction function R based on the golden sine factor, the state of the vehicle is predicted, and the state data information of the predicted vehicle is obtained.

2. The air suspension system based automatic sun visor adjustment method for a vehicle according to claim 1, wherein, The method further comprises: Q5. Based on the sun visor folding angle feasibility assessment data information, a preset threshold is set, if the sun visor folding angle feasibility assessment data information is less than the preset threshold, the sun visor folding angle meets the requirements, and the optimized sun visor folding angle data information is output, if the sun visor folding angle feasibility assessment data information is greater than the preset threshold, the sun visor folding angle does not meet the requirements, and returns to step Q3.

3. The method of claim 1, wherein: The golden sine factors ρ1, ρ2 and ρ3 of the vehicle state are, ， ， ， The constraint conditions of the smoothing parameter α of the level of the vehicle state, the smoothing parameter β of the trend of the vehicle state and the damping parameter δ of the vehicle state are, 。 4. The air suspension system based automatic sun visor adjustment method for a vehicle according to claim 1, wherein, In step Q3, the Archimedean optimization algorithm fused with Momentum and RMSProp parameters is used to optimize the folding angle of the sun visor, including: Q31. Based on the predicted vehicle state data information, the sun visor folding angle data information and the human eye position data information, the population is initialized, the population parameters and the maximum iteration number are determined, and the initialized population data information is obtained; Q32. Based on the initialized population data information, the fitness function S of the population individual is established, ， Wherein, r is the initialized population data information, γ1, γ2 and γ3 are the fitness determinants of the population individual, the fitness value of the population individual is calculated, and the fitness value data information of the population individual is obtained; Q33. Based on the fitness value data information of the population individual, the target optimization function G is established, ， Wherein, a is the fitness value data information of the population individual, η1 is the Momentum parameter of the population individual, η2 is the RMSProp parameter of the population individual, η3 is the covariance constant parameter of the population individual, the folding angle of the sun visor is optimized, and the optimized sun visor folding angle data information is obtained.

5. The method of claim 4, wherein: The Momentum parameter η1 of the population individual is, ， The RMSProp parameter η2 of the population individual is, ， The covariance constant parameter η3 of the population individual is, ， Wherein, a is the fitness value data information of the population individual.

6. A system for implementing the method of automatically adjusting the sun visor of a vehicle based on an air suspension system according to any one of claims 1 to 5, characterized in that, The system comprises: A DMS camera (11) for collecting human eye position information; A seat controller (12) for acquiring current seat position information in real time, wherein the seat position information includes seat front and rear position information, seat height information and seat backrest angle information; An electronic stability component (13) for acquiring current vehicle body slope information and six-direction acceleration information in real time; A sun visor motor (14) and a sun visor (141) connected with the sun visor motor (14) for acquiring folding angle information of the sun visor (141) in real time and driving to change the folding angle of the sun visor (141); A sun visor controller (15) is connected with the DMS camera (11), the seat controller (12), the electronic stability component (13) and the sun visor motor (14) respectively, and outputs and feeds back the folding angle information of the sun visor (141) to the sun visor motor (14) in combination with the body height information provided by the air suspension system. The controller (15) comprises a PCB board (151), a plastic shell (152) and a low-voltage connector PIN (153). The PCB board (151) is arranged inside the plastic shell (152), and the outside of the plastic shell (152) is provided with the low-voltage connector PIN (153).

7. The system of claim 6, wherein, The seat controller (12) comprises: a seat front and rear position sensor for acquiring real-time current seat front and rear position information; a seat height sensor for acquiring real-time current seat height information; a seat backrest angle sensor for acquiring real-time current seat backrest angle information; The electronic stability component (13) comprises: an accelerometer for acquiring current vehicle six-direction acceleration information; a sensing gyroscope for acquiring current vehicle body slope information.

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